HER2 Grading of Breast Cancer Patients
Our lab handles large-scale data to extract meaningful insights through statistical modeling, predictive analysis, and data visualization. We aim to support data-driven decision making.
Related Software
Open source tools and libraries for this research area
SiNuS: A Comprehensive Dataset for Singular Nuclei Segmentation for HER2 Grading of Breast Cancer
This dataset provides clinically validated annotations for singular nuclei segmentation in Dual-ISH breast cancer images (20×), essential for automated …
Related Research Projects
Explore other areas of our research
Multimodal AI for Breast Cancer Subtype Analysis and Precision Therapy Recommendation
This project aims to develop a multimodal AI system that analyzes diverse breast cancer …
Automated Diganosis Pipeline for Breast Cancer Metastasis Assessment
This research aims to develop an AI-guided automated pipeline for assessing breast cancer metastases in distant and axillary lymph nodes using …
Residual Tumor Cellularity Assessment After Neoadjuvant Therapy
Residual Tumor Cellularity (RTC) assessment after neoadjuvant therapy is essential for evaluating treatment response and …
AI-guided Solution for Selecting Ovarian Cancer Patients for Bevacizumab Monoclonal Therapy
Ovarian cancer treatment outcomes can vary significantly among patients, making personalized therapy selection crucial. This …
Interested in Collaborating?
We welcome collaborations and partnerships in this research area